A Knowledge Based Decision Support System for Supply Chain Risk Management

This paper discusses the concept of supply chain risk management (SCRM) in relation to the emerging challenges brought by globalisation and opportunities provided by the information and communication technologies (ICT) and the ability of SCRM frameworks to adapt to these latest requirements. Existing literature provides many examples of ICT platforms for supply chain optimisation and profit maximisation however there is still a research gap in relation to the existence of sufficient debate and provision of ICT tools for supply SCRM. This gap is even more intriguing since SCRM can be responsible for loss or gain of profit and the ultimate goal of enterprises should be to have resilient supply chains with automated decision making capability that can efficiently and timely deal with potential disruptions. In response to these, taking advantage of ICT developments such as knowledge discovery and data mining, and automated agent based risk management frameworks provide great perspectives for assuring business success. Having this context, this research has the following aims: 1) to perform a literature review on multi-agent systems (MAS), SCRM, decision support systems, knowledge discovery and management, and data mining, 2) to present Hi-LAB - refined MAS for SCRM, and 3) to formally design Hi-LAB, implement it and evaluate its performance